R version 2.8.0 (2008-10-20) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. Natural language support but running in an English locale R is a collaborative project with many contributors. Type 'contributors()' for more information and 'citation()' on how to cite R or R packages in publications. Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. > x <- array(list(1 + ,162556 + ,162556 + ,1081 + ,1081 + ,213118 + ,213118 + ,230380558 + ,6282929 + ,1 + ,29790 + ,29790 + ,309 + ,309 + ,81767 + ,81767 + ,25266003 + ,4324047 + ,1 + ,87550 + ,87550 + ,458 + ,458 + ,153198 + ,153198 + ,70164684 + ,4108272 + ,0 + ,84738 + ,0 + ,588 + ,0 + ,-26007 + ,0 + ,-15292116 + ,-1212617 + ,1 + ,54660 + ,54660 + ,299 + ,299 + ,126942 + ,126942 + ,37955658 + ,1485329 + ,1 + ,42634 + ,42634 + ,156 + ,156 + ,157214 + ,157214 + ,24525384 + ,1779876 + ,0 + ,40949 + ,0 + ,481 + ,0 + ,129352 + ,0 + ,62218312 + ,1367203 + ,1 + ,42312 + ,42312 + ,323 + ,323 + ,234817 + ,234817 + ,75845891 + ,2519076 + ,1 + ,37704 + ,37704 + ,452 + ,452 + ,60448 + ,60448 + ,27322496 + ,912684 + ,1 + ,16275 + ,16275 + ,109 + ,109 + ,47818 + ,47818 + ,5212162 + ,1443586 + ,0 + ,25830 + ,0 + ,115 + ,0 + ,245546 + ,0 + ,28237790 + ,1220017 + ,0 + ,12679 + ,0 + ,110 + ,0 + ,48020 + ,0 + ,5282200 + ,984885 + ,1 + ,18014 + ,18014 + ,239 + ,239 + ,-1710 + 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,73221 + ,73221 + ,805431 + ,329118) + ,dim=c(9 + ,100) + ,dimnames=list(c('Group' + ,'Costs' + ,'GrCosts' + ,'Trades' + ,'GrTrades' + ,'Dividends' + ,'GrDiv' + ,'TrDiv' + ,'Wealth ') + ,1:100)) > y <- array(NA,dim=c(9,100),dimnames=list(c('Group','Costs','GrCosts','Trades','GrTrades','Dividends','GrDiv','TrDiv','Wealth '),1:100)) > for (i in 1:dim(x)[1]) + { + for (j in 1:dim(x)[2]) + { + y[i,j] <- as.numeric(x[i,j]) + } + } > par3 = 'No Linear Trend' > par2 = 'Do not include Seasonal Dummies' > par1 = '9' > #'GNU S' R Code compiled by R2WASP v. 1.0.44 () > #Author: Prof. Dr. P. Wessa > #To cite this work: AUTHOR(S), (YEAR), YOUR SOFTWARE TITLE (vNUMBER) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_YOURPAGE.wasp/ > #Source of accompanying publication: Office for Research, Development, and Education > #Technical description: Write here your technical program description (don't use hard returns!) > library(lattice) > library(lmtest) Loading required package: zoo Attaching package: 'zoo' The following object(s) are masked from package:base : as.Date.numeric > n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test > par1 <- as.numeric(par1) > x <- t(y) > k <- length(x[1,]) > n <- length(x[,1]) > x1 <- cbind(x[,par1], x[,1:k!=par1]) > mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) > colnames(x1) <- mycolnames #colnames(x)[par1] > x <- x1 > if (par3 == 'First Differences'){ + x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) + for (i in 1:n-1) { + for (j in 1:k) { + x2[i,j] <- x[i+1,j] - x[i,j] + } + } + x <- x2 + } > if (par2 == 'Include Monthly Dummies'){ + x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) + for (i in 1:11){ + x2[seq(i,n,12),i] <- 1 + } + x <- cbind(x, x2) + } > if (par2 == 'Include Quarterly Dummies'){ + x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) + for (i in 1:3){ + x2[seq(i,n,4),i] <- 1 + } + x <- cbind(x, x2) + } > k <- length(x[1,]) > if (par3 == 'Linear Trend'){ + x <- cbind(x, c(1:n)) + colnames(x)[k+1] <- 't' + } > x Wealth\r Group Costs GrCosts Trades GrTrades Dividends GrDiv TrDiv 1 6282929 1 162556 162556 1081 1081 213118 213118 230380558 2 4324047 1 29790 29790 309 309 81767 81767 25266003 3 4108272 1 87550 87550 458 458 153198 153198 70164684 4 -1212617 0 84738 0 588 0 -26007 0 -15292116 5 1485329 1 54660 54660 299 299 126942 126942 37955658 6 1779876 1 42634 42634 156 156 157214 157214 24525384 7 1367203 0 40949 0 481 0 129352 0 62218312 8 2519076 1 42312 42312 323 323 234817 234817 75845891 9 912684 1 37704 37704 452 452 60448 60448 27322496 10 1443586 1 16275 16275 109 109 47818 47818 5212162 11 1220017 0 25830 0 115 0 245546 0 28237790 12 984885 0 12679 0 110 0 48020 0 5282200 13 1457425 1 18014 18014 239 239 -1710 -1710 -408690 14 -572920 0 43556 0 247 0 32648 0 8064056 15 929144 1 24524 24524 497 497 95350 95350 47388950 16 1151176 0 6532 0 103 0 151352 0 15589256 17 790090 0 7123 0 109 0 288170 0 31410530 18 774497 1 20813 20813 502 502 114337 114337 57397174 19 990576 1 37597 37597 248 248 37884 37884 9395232 20 454195 0 17821 0 373 0 122844 0 45820812 21 876607 1 12988 12988 119 119 82340 82340 9798460 22 711969 1 22330 22330 84 84 79801 79801 6703284 23 702380 0 13326 0 102 0 165548 0 16885896 24 264449 0 16189 0 295 0 116384 0 34333280 25 450033 0 7146 0 105 0 134028 0 14072940 26 541063 0 15824 0 64 0 63838 0 4085632 27 588864 1 26088 26088 267 267 74996 74996 20023932 28 -37216 0 11326 0 129 0 31080 0 4009320 29 783310 0 8568 0 37 0 32168 0 1190216 30 467359 0 14416 0 361 0 49857 0 17998377 31 688779 1 3369 3369 28 28 87161 87161 2440508 32 608419 1 11819 11819 85 85 106113 106113 9019605 33 696348 1 6620 6620 44 44 80570 80570 3545080 34 597793 1 4519 4519 49 49 102129 102129 5004321 35 821730 0 2220 0 22 0 301670 0 6636740 36 377934 0 18562 0 155 0 102313 0 15858515 37 651939 0 10327 0 91 0 88577 0 8060507 38 697458 1 5336 5336 81 81 112477 112477 9110637 39 700368 1 2365 2365 79 79 191778 191778 15150462 40 225986 0 4069 0 145 0 79804 0 11571580 41 348695 0 7710 0 816 0 128294 0 104687904 42 373683 0 13718 0 61 0 96448 0 5883328 43 501709 0 4525 0 226 0 93811 0 21201286 44 413743 0 6869 0 105 0 117520 0 12339600 45 379825 0 4628 0 62 0 69159 0 4287858 46 336260 1 3653 3653 24 24 101792 101792 2443008 47 636765 1 1265 1265 26 26 210568 210568 5474768 48 481231 1 7489 7489 322 322 136996 136996 44112712 49 469107 0 4901 0 84 0 121920 0 10241280 50 211928 0 2284 0 33 0 76403 0 2521299 51 563925 1 3160 3160 108 108 108094 108094 11674152 52 511939 1 4150 4150 150 150 134759 134759 20213850 53 521016 1 7285 7285 115 115 188873 188873 21720395 54 543856 1 1134 1134 162 162 146216 146216 23686992 55 329304 1 4658 4658 158 158 156608 156608 24744064 56 423262 0 2384 0 97 0 61348 0 5950756 57 509665 0 3748 0 9 0 50350 0 453150 58 455881 0 5371 0 66 0 87720 0 5789520 59 367772 0 1285 0 107 0 99489 0 10645323 60 406339 1 9327 9327 101 101 87419 87419 8829319 61 493408 1 5565 5565 47 47 94355 94355 4434685 62 232942 0 1528 0 38 0 60326 0 2292388 63 416002 1 3122 3122 34 34 94670 94670 3218780 64 337430 1 7317 7317 84 84 82425 82425 6923700 65 361517 0 2675 0 79 0 59017 0 4662343 66 360962 0 13253 0 947 0 90829 0 86015063 67 235561 0 880 0 74 0 80791 0 5978534 68 408247 1 2053 2053 53 53 100423 100423 5322419 69 450296 0 1424 0 94 0 131116 0 12324904 70 418799 1 4036 4036 63 63 100269 100269 6316947 71 247405 1 3045 3045 58 58 27330 27330 1585140 72 378519 0 5119 0 49 0 39039 0 1912911 73 326638 0 1431 0 34 0 106885 0 3634090 74 328233 0 554 0 11 0 79285 0 872135 75 386225 0 1975 0 35 0 118881 0 4160835 76 283662 1 1286 1286 17 17 77623 77623 1319591 77 370225 0 1012 0 47 0 114768 0 5394096 78 269236 0 810 0 43 0 74015 0 3182645 79 365732 0 1280 0 117 0 69465 0 8127405 80 420383 1 666 666 171 171 117869 117869 20155599 81 345811 0 1380 0 26 0 60982 0 1585532 82 431809 1 4608 4608 73 73 90131 90131 6579563 83 418876 0 876 0 59 0 138971 0 8199289 84 297476 0 814 0 18 0 39625 0 713250 85 416776 0 514 0 15 0 102725 0 1540875 86 357257 1 5692 5692 72 72 64239 64239 4625208 87 458343 0 3642 0 86 0 90262 0 7762532 88 388386 0 540 0 14 0 103960 0 1455440 89 358934 0 2099 0 64 0 106611 0 6823104 90 407560 0 567 0 11 0 103345 0 1136795 91 392558 0 2001 0 52 0 95551 0 4968652 92 373177 1 2949 2949 41 41 82903 82903 3399023 93 428370 0 2253 0 99 0 63593 0 6295707 94 369419 1 6533 6533 75 75 126910 126910 9518250 95 358649 0 1889 0 45 0 37527 0 1688715 96 376641 1 3055 3055 43 43 60247 60247 2590621 97 467427 0 272 0 8 0 112995 0 903960 98 364885 1 1414 1414 198 198 70184 70184 13896432 99 436230 0 2564 0 22 0 130140 0 2863080 100 329118 1 1383 1383 11 11 73221 73221 805431 > k <- length(x[1,]) > df <- as.data.frame(x) > (mylm <- lm(df)) Call: lm(formula = df) Coefficients: (Intercept) Group Costs GrCosts Trades GrTrades 2.472e+05 1.824e+05 -3.390e+00 3.661e+01 -9.509e+02 -6.481e+01 Dividends GrDiv TrDiv 2.256e+00 -2.694e+00 8.814e-03 > (mysum <- summary(mylm)) Call: lm(formula = df) Residuals: Min 1Q Median 3Q Max -735059 -157487 -70014 84406 3031952 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 2.472e+05 1.378e+05 1.794 0.0762 . Group 1.824e+05 2.212e+05 0.824 0.4119 Costs -3.390e+00 5.733e+00 -0.591 0.5558 GrCosts 3.661e+01 8.427e+00 4.344 3.63e-05 *** Trades -9.509e+02 6.782e+02 -1.402 0.1643 GrTrades -6.481e+01 7.606e+02 -0.085 0.9323 Dividends 2.256e+00 1.192e+00 1.892 0.0616 . GrDiv -2.694e+00 1.791e+00 -1.504 0.1361 TrDiv 8.814e-03 5.171e-03 1.705 0.0917 . --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 427500 on 91 degrees of freedom Multiple R-squared: 0.7807, Adjusted R-squared: 0.7614 F-statistic: 40.5 on 8 and 91 DF, p-value: < 2.2e-16 > if (n > n25) { + kp3 <- k + 3 + nmkm3 <- n - k - 3 + gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) + numgqtests <- 0 + numsignificant1 <- 0 + numsignificant5 <- 0 + numsignificant10 <- 0 + for (mypoint in kp3:nmkm3) { + j <- 0 + numgqtests <- numgqtests + 1 + for (myalt in c('greater', 'two.sided', 'less')) { + j <- j + 1 + gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value + } + if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 + if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 + } + gqarr + } [,1] [,2] [,3] [1,] 1.0000000 1.033658e-23 5.168288e-24 [2,] 1.0000000 4.397215e-26 2.198608e-26 [3,] 1.0000000 1.143513e-29 5.717566e-30 [4,] 1.0000000 7.555857e-30 3.777929e-30 [5,] 1.0000000 6.450887e-33 3.225443e-33 [6,] 1.0000000 1.016877e-32 5.084385e-33 [7,] 1.0000000 2.891019e-32 1.445510e-32 [8,] 1.0000000 9.960913e-33 4.980457e-33 [9,] 1.0000000 2.217084e-32 1.108542e-32 [10,] 1.0000000 2.956038e-33 1.478019e-33 [11,] 1.0000000 3.071784e-33 1.535892e-33 [12,] 1.0000000 1.239624e-32 6.198118e-33 [13,] 1.0000000 1.474330e-32 7.371650e-33 [14,] 1.0000000 9.695610e-32 4.847805e-32 [15,] 1.0000000 5.561865e-31 2.780933e-31 [16,] 1.0000000 1.089926e-30 5.449632e-31 [17,] 1.0000000 1.644172e-32 8.220858e-33 [18,] 1.0000000 5.494118e-35 2.747059e-35 [19,] 1.0000000 3.920701e-34 1.960350e-34 [20,] 1.0000000 1.044335e-34 5.221673e-35 [21,] 1.0000000 4.471712e-34 2.235856e-34 [22,] 1.0000000 3.682900e-35 1.841450e-35 [23,] 1.0000000 5.396272e-35 2.698136e-35 [24,] 1.0000000 1.522614e-34 7.613068e-35 [25,] 1.0000000 3.570169e-34 1.785085e-34 [26,] 1.0000000 1.509830e-34 7.549152e-35 [27,] 1.0000000 5.165974e-36 2.582987e-36 [28,] 1.0000000 1.108873e-35 5.544364e-36 [29,] 1.0000000 9.072300e-36 4.536150e-36 [30,] 1.0000000 5.308463e-35 2.654231e-35 [31,] 1.0000000 5.995773e-35 2.997887e-35 [32,] 1.0000000 1.315342e-34 6.576711e-35 [33,] 1.0000000 7.240782e-34 3.620391e-34 [34,] 1.0000000 5.862044e-33 2.931022e-33 [35,] 1.0000000 2.812520e-32 1.406260e-32 [36,] 1.0000000 2.635542e-31 1.317771e-31 [37,] 1.0000000 1.523154e-30 7.615768e-31 [38,] 1.0000000 1.413838e-29 7.069189e-30 [39,] 1.0000000 4.123533e-30 2.061766e-30 [40,] 1.0000000 3.230425e-30 1.615213e-30 [41,] 1.0000000 1.450701e-29 7.253506e-30 [42,] 1.0000000 1.349946e-28 6.749730e-29 [43,] 1.0000000 7.755483e-29 3.877741e-29 [44,] 1.0000000 2.834822e-28 1.417411e-28 [45,] 1.0000000 1.507356e-27 7.536782e-28 [46,] 1.0000000 9.289898e-28 4.644949e-28 [47,] 1.0000000 1.024469e-26 5.122345e-27 [48,] 1.0000000 1.070649e-25 5.353243e-26 [49,] 1.0000000 9.611115e-25 4.805557e-25 [50,] 1.0000000 1.428948e-24 7.144740e-25 [51,] 1.0000000 1.798383e-24 8.991914e-25 [52,] 1.0000000 1.596682e-23 7.983410e-24 [53,] 1.0000000 1.320938e-22 6.604692e-23 [54,] 1.0000000 1.478523e-21 7.392613e-22 [55,] 1.0000000 1.293218e-20 6.466089e-21 [56,] 1.0000000 4.557225e-21 2.278613e-21 [57,] 1.0000000 4.839985e-20 2.419992e-20 [58,] 1.0000000 3.417178e-19 1.708589e-19 [59,] 1.0000000 3.241690e-18 1.620845e-18 [60,] 1.0000000 1.933736e-17 9.668682e-18 [61,] 1.0000000 2.138713e-16 1.069357e-16 [62,] 1.0000000 7.481749e-16 3.740874e-16 [63,] 1.0000000 7.177123e-15 3.588561e-15 [64,] 1.0000000 5.537067e-14 2.768533e-14 [65,] 1.0000000 1.980990e-13 9.904948e-14 [66,] 1.0000000 1.738649e-12 8.693246e-13 [67,] 1.0000000 1.691614e-12 8.458072e-13 [68,] 1.0000000 1.707892e-11 8.539462e-12 [69,] 1.0000000 1.896702e-11 9.483511e-12 [70,] 1.0000000 2.810031e-10 1.405015e-10 [71,] 1.0000000 7.951780e-10 3.975890e-10 [72,] 1.0000000 1.102868e-08 5.514338e-09 [73,] 0.9999999 1.650593e-07 8.252964e-08 [74,] 0.9999989 2.202584e-06 1.101292e-06 [75,] 0.9999920 1.606091e-05 8.030457e-06 [76,] 0.9999911 1.775782e-05 8.878910e-06 [77,] 0.9999348 1.303868e-04 6.519338e-05 > postscript(file="/var/www/html/freestat/rcomp/tmp/1845n1291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') > points(x[,1]-mysum$resid) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/21dn81291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/31dn81291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/41dn81291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/51dn81291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') > qqline(mysum$resid) > grid() > dev.off() null device 1 > (myerror <- as.ts(mysum$resid)) Time Series: Start = 1 End = 100 Frequency = 1 1 2 3 4 5 6 -385354.276 3031951.861 684521.405 -419917.413 -735058.574 -54673.022 7 8 9 10 11 12 876008.912 446465.076 -524497.192 559157.609 366925.180 730410.155 13 14 15 16 17 18 675130.635 -582281.337 -186143.292 545236.147 -256257.720 -292351.579 19 20 21 22 23 24 -502111.672 -58892.047 86204.203 -398109.843 75068.519 -212510.435 25 26 27 28 29 30 -99474.932 228372.697 -579685.791 -228775.340 517314.639 341210.922 31 32 33 34 35 36 192414.104 -160414.226 95629.064 68514.934 -136059.940 -29514.627 37 38 39 40 41 42 255437.451 141881.057 222926.524 -151541.907 -308606.418 -38414.301 43 44 45 46 47 48 86268.023 -84183.615 13486.942 -167216.843 235540.637 -198863.700 49 50 51 52 53 54 -46891.407 -190703.858 83533.225 -22273.982 -142461.650 96411.623 55 56 57 58 59 60 -244021.200 85560.439 166181.431 40755.448 -91572.997 -269978.532 61 62 63 64 65 66 -71027.436 -129211.004 -69636.892 -274781.047 24301.778 96124.721 67 68 69 70 71 72 -173218.164 -38610.124 -107094.288 -92600.863 -226384.569 90369.202 73 74 75 76 77 78 -156511.488 -93148.911 -125835.323 -148983.735 -135281.252 -129326.659 79 80 81 82 83 84 5806.934 16339.721 -23503.635 -95186.842 -155009.175 -25494.132 85 86 87 88 89 90 -59713.673 -200870.123 33247.147 -90999.522 -120915.516 -70390.488 91 92 93 94 95 96 -57736.898 -106346.630 84020.761 -229284.273 61131.895 -107166.188 97 98 99 100 -34094.584 -2288.539 -100156.337 -110239.042 > postscript(file="/var/www/html/freestat/rcomp/tmp/6u44t1291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > dum <- cbind(lag(myerror,k=1),myerror) > dum Time Series: Start = 0 End = 100 Frequency = 1 lag(myerror, k = 1) myerror 0 -385354.276 NA 1 3031951.861 -385354.276 2 684521.405 3031951.861 3 -419917.413 684521.405 4 -735058.574 -419917.413 5 -54673.022 -735058.574 6 876008.912 -54673.022 7 446465.076 876008.912 8 -524497.192 446465.076 9 559157.609 -524497.192 10 366925.180 559157.609 11 730410.155 366925.180 12 675130.635 730410.155 13 -582281.337 675130.635 14 -186143.292 -582281.337 15 545236.147 -186143.292 16 -256257.720 545236.147 17 -292351.579 -256257.720 18 -502111.672 -292351.579 19 -58892.047 -502111.672 20 86204.203 -58892.047 21 -398109.843 86204.203 22 75068.519 -398109.843 23 -212510.435 75068.519 24 -99474.932 -212510.435 25 228372.697 -99474.932 26 -579685.791 228372.697 27 -228775.340 -579685.791 28 517314.639 -228775.340 29 341210.922 517314.639 30 192414.104 341210.922 31 -160414.226 192414.104 32 95629.064 -160414.226 33 68514.934 95629.064 34 -136059.940 68514.934 35 -29514.627 -136059.940 36 255437.451 -29514.627 37 141881.057 255437.451 38 222926.524 141881.057 39 -151541.907 222926.524 40 -308606.418 -151541.907 41 -38414.301 -308606.418 42 86268.023 -38414.301 43 -84183.615 86268.023 44 13486.942 -84183.615 45 -167216.843 13486.942 46 235540.637 -167216.843 47 -198863.700 235540.637 48 -46891.407 -198863.700 49 -190703.858 -46891.407 50 83533.225 -190703.858 51 -22273.982 83533.225 52 -142461.650 -22273.982 53 96411.623 -142461.650 54 -244021.200 96411.623 55 85560.439 -244021.200 56 166181.431 85560.439 57 40755.448 166181.431 58 -91572.997 40755.448 59 -269978.532 -91572.997 60 -71027.436 -269978.532 61 -129211.004 -71027.436 62 -69636.892 -129211.004 63 -274781.047 -69636.892 64 24301.778 -274781.047 65 96124.721 24301.778 66 -173218.164 96124.721 67 -38610.124 -173218.164 68 -107094.288 -38610.124 69 -92600.863 -107094.288 70 -226384.569 -92600.863 71 90369.202 -226384.569 72 -156511.488 90369.202 73 -93148.911 -156511.488 74 -125835.323 -93148.911 75 -148983.735 -125835.323 76 -135281.252 -148983.735 77 -129326.659 -135281.252 78 5806.934 -129326.659 79 16339.721 5806.934 80 -23503.635 16339.721 81 -95186.842 -23503.635 82 -155009.175 -95186.842 83 -25494.132 -155009.175 84 -59713.673 -25494.132 85 -200870.123 -59713.673 86 33247.147 -200870.123 87 -90999.522 33247.147 88 -120915.516 -90999.522 89 -70390.488 -120915.516 90 -57736.898 -70390.488 91 -106346.630 -57736.898 92 84020.761 -106346.630 93 -229284.273 84020.761 94 61131.895 -229284.273 95 -107166.188 61131.895 96 -34094.584 -107166.188 97 -2288.539 -34094.584 98 -100156.337 -2288.539 99 -110239.042 -100156.337 100 NA -110239.042 > dum1 <- dum[2:length(myerror),] > dum1 lag(myerror, k = 1) myerror [1,] 3031951.861 -385354.276 [2,] 684521.405 3031951.861 [3,] -419917.413 684521.405 [4,] -735058.574 -419917.413 [5,] -54673.022 -735058.574 [6,] 876008.912 -54673.022 [7,] 446465.076 876008.912 [8,] -524497.192 446465.076 [9,] 559157.609 -524497.192 [10,] 366925.180 559157.609 [11,] 730410.155 366925.180 [12,] 675130.635 730410.155 [13,] -582281.337 675130.635 [14,] -186143.292 -582281.337 [15,] 545236.147 -186143.292 [16,] -256257.720 545236.147 [17,] -292351.579 -256257.720 [18,] -502111.672 -292351.579 [19,] -58892.047 -502111.672 [20,] 86204.203 -58892.047 [21,] -398109.843 86204.203 [22,] 75068.519 -398109.843 [23,] -212510.435 75068.519 [24,] -99474.932 -212510.435 [25,] 228372.697 -99474.932 [26,] -579685.791 228372.697 [27,] -228775.340 -579685.791 [28,] 517314.639 -228775.340 [29,] 341210.922 517314.639 [30,] 192414.104 341210.922 [31,] -160414.226 192414.104 [32,] 95629.064 -160414.226 [33,] 68514.934 95629.064 [34,] -136059.940 68514.934 [35,] -29514.627 -136059.940 [36,] 255437.451 -29514.627 [37,] 141881.057 255437.451 [38,] 222926.524 141881.057 [39,] -151541.907 222926.524 [40,] -308606.418 -151541.907 [41,] -38414.301 -308606.418 [42,] 86268.023 -38414.301 [43,] -84183.615 86268.023 [44,] 13486.942 -84183.615 [45,] -167216.843 13486.942 [46,] 235540.637 -167216.843 [47,] -198863.700 235540.637 [48,] -46891.407 -198863.700 [49,] -190703.858 -46891.407 [50,] 83533.225 -190703.858 [51,] -22273.982 83533.225 [52,] -142461.650 -22273.982 [53,] 96411.623 -142461.650 [54,] -244021.200 96411.623 [55,] 85560.439 -244021.200 [56,] 166181.431 85560.439 [57,] 40755.448 166181.431 [58,] -91572.997 40755.448 [59,] -269978.532 -91572.997 [60,] -71027.436 -269978.532 [61,] -129211.004 -71027.436 [62,] -69636.892 -129211.004 [63,] -274781.047 -69636.892 [64,] 24301.778 -274781.047 [65,] 96124.721 24301.778 [66,] -173218.164 96124.721 [67,] -38610.124 -173218.164 [68,] -107094.288 -38610.124 [69,] -92600.863 -107094.288 [70,] -226384.569 -92600.863 [71,] 90369.202 -226384.569 [72,] -156511.488 90369.202 [73,] -93148.911 -156511.488 [74,] -125835.323 -93148.911 [75,] -148983.735 -125835.323 [76,] -135281.252 -148983.735 [77,] -129326.659 -135281.252 [78,] 5806.934 -129326.659 [79,] 16339.721 5806.934 [80,] -23503.635 16339.721 [81,] -95186.842 -23503.635 [82,] -155009.175 -95186.842 [83,] -25494.132 -155009.175 [84,] -59713.673 -25494.132 [85,] -200870.123 -59713.673 [86,] 33247.147 -200870.123 [87,] -90999.522 33247.147 [88,] -120915.516 -90999.522 [89,] -70390.488 -120915.516 [90,] -57736.898 -70390.488 [91,] -106346.630 -57736.898 [92,] 84020.761 -106346.630 [93,] -229284.273 84020.761 [94,] 61131.895 -229284.273 [95,] -107166.188 61131.895 [96,] -34094.584 -107166.188 [97,] -2288.539 -34094.584 [98,] -100156.337 -2288.539 [99,] -110239.042 -100156.337 > z <- as.data.frame(dum1) > z lag(myerror, k = 1) myerror 1 3031951.861 -385354.276 2 684521.405 3031951.861 3 -419917.413 684521.405 4 -735058.574 -419917.413 5 -54673.022 -735058.574 6 876008.912 -54673.022 7 446465.076 876008.912 8 -524497.192 446465.076 9 559157.609 -524497.192 10 366925.180 559157.609 11 730410.155 366925.180 12 675130.635 730410.155 13 -582281.337 675130.635 14 -186143.292 -582281.337 15 545236.147 -186143.292 16 -256257.720 545236.147 17 -292351.579 -256257.720 18 -502111.672 -292351.579 19 -58892.047 -502111.672 20 86204.203 -58892.047 21 -398109.843 86204.203 22 75068.519 -398109.843 23 -212510.435 75068.519 24 -99474.932 -212510.435 25 228372.697 -99474.932 26 -579685.791 228372.697 27 -228775.340 -579685.791 28 517314.639 -228775.340 29 341210.922 517314.639 30 192414.104 341210.922 31 -160414.226 192414.104 32 95629.064 -160414.226 33 68514.934 95629.064 34 -136059.940 68514.934 35 -29514.627 -136059.940 36 255437.451 -29514.627 37 141881.057 255437.451 38 222926.524 141881.057 39 -151541.907 222926.524 40 -308606.418 -151541.907 41 -38414.301 -308606.418 42 86268.023 -38414.301 43 -84183.615 86268.023 44 13486.942 -84183.615 45 -167216.843 13486.942 46 235540.637 -167216.843 47 -198863.700 235540.637 48 -46891.407 -198863.700 49 -190703.858 -46891.407 50 83533.225 -190703.858 51 -22273.982 83533.225 52 -142461.650 -22273.982 53 96411.623 -142461.650 54 -244021.200 96411.623 55 85560.439 -244021.200 56 166181.431 85560.439 57 40755.448 166181.431 58 -91572.997 40755.448 59 -269978.532 -91572.997 60 -71027.436 -269978.532 61 -129211.004 -71027.436 62 -69636.892 -129211.004 63 -274781.047 -69636.892 64 24301.778 -274781.047 65 96124.721 24301.778 66 -173218.164 96124.721 67 -38610.124 -173218.164 68 -107094.288 -38610.124 69 -92600.863 -107094.288 70 -226384.569 -92600.863 71 90369.202 -226384.569 72 -156511.488 90369.202 73 -93148.911 -156511.488 74 -125835.323 -93148.911 75 -148983.735 -125835.323 76 -135281.252 -148983.735 77 -129326.659 -135281.252 78 5806.934 -129326.659 79 16339.721 5806.934 80 -23503.635 16339.721 81 -95186.842 -23503.635 82 -155009.175 -95186.842 83 -25494.132 -155009.175 84 -59713.673 -25494.132 85 -200870.123 -59713.673 86 33247.147 -200870.123 87 -90999.522 33247.147 88 -120915.516 -90999.522 89 -70390.488 -120915.516 90 -57736.898 -70390.488 91 -106346.630 -57736.898 92 84020.761 -106346.630 93 -229284.273 84020.761 94 61131.895 -229284.273 95 -107166.188 61131.895 96 -34094.584 -107166.188 97 -2288.539 -34094.584 98 -100156.337 -2288.539 99 -110239.042 -100156.337 > plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') > lines(lowess(z)) > abline(lm(z)) > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/74w3w1291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/84w3w1291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') > grid() > dev.off() null device 1 > postscript(file="/var/www/html/freestat/rcomp/tmp/94w3w1291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) > opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) > plot(mylm, las = 1, sub='Residual Diagnostics') > par(opar) > dev.off() null device 1 > if (n > n25) { + postscript(file="/var/www/html/freestat/rcomp/tmp/10fn2h1291364961.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) + plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') + grid() + dev.off() + } null device 1 > > #Note: the /var/www/html/freestat/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab > load(file="/var/www/html/freestat/rcomp/createtable") > > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) > a<-table.row.end(a) > myeq <- colnames(x)[1] > myeq <- paste(myeq, '[t] = ', sep='') > for (i in 1:k){ + if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') + myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') + if (rownames(mysum$coefficients)[i] != '(Intercept)') { + myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') + if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') + } + } > myeq <- paste(myeq, ' + e[t]') > a<-table.row.start(a) > a<-table.element(a, myeq) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/110n1n1291364961.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a,'Variable',header=TRUE) > a<-table.element(a,'Parameter',header=TRUE) > a<-table.element(a,'S.D.',header=TRUE) > a<-table.element(a,'T-STAT
H0: parameter = 0',header=TRUE) > a<-table.element(a,'2-tail p-value',header=TRUE) > a<-table.element(a,'1-tail p-value',header=TRUE) > a<-table.row.end(a) > for (i in 1:k){ + a<-table.row.start(a) + a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) + a<-table.element(a,mysum$coefficients[i,1]) + a<-table.element(a, round(mysum$coefficients[i,2],6)) + a<-table.element(a, round(mysum$coefficients[i,3],4)) + a<-table.element(a, round(mysum$coefficients[i,4],6)) + a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/124ohb1291364961.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple R',1,TRUE) > a<-table.element(a, sqrt(mysum$r.squared)) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'R-squared',1,TRUE) > a<-table.element(a, mysum$r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Adjusted R-squared',1,TRUE) > a<-table.element(a, mysum$adj.r.squared) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (value)',1,TRUE) > a<-table.element(a, mysum$fstatistic[1]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[2]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) > a<-table.element(a, mysum$fstatistic[3]) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'p-value',1,TRUE) > a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Residual Standard Deviation',1,TRUE) > a<-table.element(a, mysum$sigma) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Sum Squared Residuals',1,TRUE) > a<-table.element(a, sum(myerror*myerror)) > a<-table.row.end(a) > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/13tpwm1291364961.tab") > a<-table.start() > a<-table.row.start(a) > a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) > a<-table.row.end(a) > a<-table.row.start(a) > a<-table.element(a, 'Time or Index', 1, TRUE) > a<-table.element(a, 'Actuals', 1, TRUE) > a<-table.element(a, 'Interpolation
Forecast', 1, TRUE) > a<-table.element(a, 'Residuals
Prediction Error', 1, TRUE) > a<-table.row.end(a) > for (i in 1:n) { + a<-table.row.start(a) + a<-table.element(a,i, 1, TRUE) + a<-table.element(a,x[i]) + a<-table.element(a,x[i]-mysum$resid[i]) + a<-table.element(a,mysum$resid[i]) + a<-table.row.end(a) + } > a<-table.end(a) > table.save(a,file="/var/www/html/freestat/rcomp/tmp/14lywp1291364961.tab") > if (n > n25) { + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'p-values',header=TRUE) + a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'breakpoint index',header=TRUE) + a<-table.element(a,'greater',header=TRUE) + a<-table.element(a,'2-sided',header=TRUE) + a<-table.element(a,'less',header=TRUE) + a<-table.row.end(a) + for (mypoint in kp3:nmkm3) { + a<-table.row.start(a) + a<-table.element(a,mypoint,header=TRUE) + a<-table.element(a,gqarr[mypoint-kp3+1,1]) + a<-table.element(a,gqarr[mypoint-kp3+1,2]) + a<-table.element(a,gqarr[mypoint-kp3+1,3]) + a<-table.row.end(a) + } + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/15phcv1291364961.tab") + a<-table.start() + a<-table.row.start(a) + a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'Description',header=TRUE) + a<-table.element(a,'# significant tests',header=TRUE) + a<-table.element(a,'% significant tests',header=TRUE) + a<-table.element(a,'OK/NOK',header=TRUE) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'1% type I error level',header=TRUE) + a<-table.element(a,numsignificant1) + a<-table.element(a,numsignificant1/numgqtests) + if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'5% type I error level',header=TRUE) + a<-table.element(a,numsignificant5) + a<-table.element(a,numsignificant5/numgqtests) + if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.row.start(a) + a<-table.element(a,'10% type I error level',header=TRUE) + a<-table.element(a,numsignificant10) + a<-table.element(a,numsignificant10/numgqtests) + if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' + a<-table.element(a,dum) + a<-table.row.end(a) + a<-table.end(a) + table.save(a,file="/var/www/html/freestat/rcomp/tmp/1638a41291364961.tab") + } > > try(system("convert tmp/1845n1291364961.ps tmp/1845n1291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/21dn81291364961.ps tmp/21dn81291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/31dn81291364961.ps tmp/31dn81291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/41dn81291364961.ps tmp/41dn81291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/51dn81291364961.ps tmp/51dn81291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/6u44t1291364961.ps tmp/6u44t1291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/74w3w1291364961.ps tmp/74w3w1291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/84w3w1291364961.ps tmp/84w3w1291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/94w3w1291364961.ps tmp/94w3w1291364961.png",intern=TRUE)) character(0) > try(system("convert tmp/10fn2h1291364961.ps tmp/10fn2h1291364961.png",intern=TRUE)) character(0) > > > proc.time() user system elapsed 4.632 2.494 4.980